Using BMEcat Catalogs as a Lever for Product Master Data on the Semantic Web

Stolz, Alex; Rodriguez-Castro, Benedicto; Hepp, Martin

doi:10.1007/978-3-642-38288-8_42

Cited by 10 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach is based on a service hub that allows data exchange and data transformation, and separates between a certain and uncertain knowledge repository. Stolz et al presented another integration-focused approach [33]. This work consisted of a transformation from the standard catalogue format BMEcat to the already mentioned GoodRelations ontology.…”

Section: Semantic Technologies and Information Systemsmentioning

confidence: 99%

Ontology-Based Big Data Management

Eine

Jurisch

Quint

2017

Systems

View full text Add to dashboard Cite

Big data management is no longer an issue for large enterprises only; it has also become a challenge for small and middle-sized enterprises, too. Today, enterprises have to handle business data and processes of increasing complexity that are almost entirely electronic in nature, regardless of enterprises' size. Enterprises' information systems need functions based on specific technologies to be able to reduce and interpret the complexity of business data and processes. This paper pursues the question: how can state-of-the-art information systems be improved by the use of semantic technologies, and particularly ontologies? For this purpose, three use cases of information systems that could be improved are described, and approaches based on semantic technologies and ontologies are proposed. The selected use cases relate to data integration, data quality, and business process integration.

show abstract

Section: Semantic Technologies and Information Systemsmentioning

confidence: 99%

Ontology-Based Big Data Management

Eine

Jurisch

Quint

2017

Systems

View full text Add to dashboard Cite

show abstract

“…Those files were converted into JSON-LD syntax since both RDF/XML and JSON-LD are capable to serialize an RDF graph. The translation was done using the RDF Translator [27]. The frame shown in Listing 6 was used together with a translated CIM Profile as an input to the Extended Framing Algorithm.…”

Section: The Rdfs Test Scenariomentioning

confidence: 99%

Extending JSON-LD Framing Capabilities

Nenadić¹,

Gavric²,

Lendak³

2017

ACTA POLYTECH HUNG

View full text Add to dashboard Cite

Today, with the increasing popularity of JSON-LD on the Web, there is a need for transformation and extraction of such structured data. In this paper, the authors propose extensions of the JSON-LD Framing specification which are able to create a tree layout based on recursive application of prioritized inverse relationships defined in a frame. The extensions include recursive application of reverse framing, a new @priority keyword which prioritizes reverse properties, a new embedding rule defined with the @first keyword, and the new @reverseRoots keyword used for filtering the result hierarchies of full-length. The proposed Extended Framing Algorithm, together with an extended frame, can be applied on arbitrary JSON-LD input files regardless of the length of its reverse hierarchy chains present in the frame. The proposed solution was tested on JSON-LD documents containing the ENTSO-E CIM Profiles. The two test scenarios were selected because of their complexity and size, each of them containing the ENTSO-E CIM Profiles expressed in CIM RDF Schema and OWL 2 Schema, respectively.

show abstract

“…Some examples of catalog group hierarchies considered in the context of this paper are proprietary product taxonomies like the Google product taxonomy [16] and the productpilot category system [17] (the proprietary category structure of a subsidiary of Messe Frankfurt), as well as product categories transmitted via catalog exchange formats like BMEcat 6 [18]. The latter can take advantage of both product categorization standards and catalog group structures in order to organize types of products and services and to contribute additional granularity in terms of semantic descriptions [19].…”

Section: Proprietary Product Category Systemsmentioning

confidence: 99%

PCS2OWL: A Generic Approach for Deriving Web Ontologies from Product Classification Systems

Stolz

Rodriguez-Castro²,

Radinger

et al. 2014

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Abstract. The classification of products and services enables reliable and efficient electronic exchanges of product data across organizations. Many companies classify products (a) according to generic or industryspecific product classification standards, or (b) by using proprietary category systems. Such classification systems often contain thousands of product classes that are updated over time. This implies a large quantity of useful product category information for e-commerce applications on the Web of Data. Thus, instead of building up product ontologies from scratch, which is costly, tedious, error-prone, and high-maintenance, it is generally easier to derive them from existing classifications. In this paper, we (1) describe a generic, semi-automated method for deriving OWL ontologies from product classification standards and proprietary category systems. Moreover, we (2) show that our approach generates logically and semantically correct vocabularies, and (3) present the practical benefit of our approach. The resulting product ontologies are compatible with the GoodRelations vocabulary for e-commerce and with schema.org and can be used to enrich product and offer descriptions on the Semantic Web with granular product type information from existing data sources.

show abstract

Using BMEcat Catalogs as a Lever for Product Master Data on the Semantic Web

Cited by 10 publications

References 12 publications

Ontology-Based Big Data Management

Ontology-Based Big Data Management

Extending JSON-LD Framing Capabilities

PCS2OWL: A Generic Approach for Deriving Web Ontologies from Product Classification Systems

Contact Info

Product

Resources

About